Nature's beauty versus urban bustle: Chinese folk music influences food choices by inducing mental imagery of different scenes.

Previous research has demonstrated that music can impact people's food choices by triggering emotional states. We reported two virtual reality (VR) experiments designed to examine how Chinese folk music influences people's food choices by inducing mental imagery of different scenes. In both experiments, young healthy Chinese participants were asked to select three dishes from an assortment of two meat and two vegetable dishes while listening to Chinese folk music that could elicit mental imagery of nature or urban scenes. The results of Experiment 1 revealed that they chose vegetable-forward meals more frequently while listening to Chinese folk music eliciting mental imagery of nature versus urban scenes. In Experiment 2, the participants were randomly divided into three groups, in which the prevalence of their mental imagery was enhanced, moderately suppressed, or strongly suppressed by performing different tasks while listening to the music pieces. We replicated the results of Experiment 1 when the participants' mental imagery was enhanced, whereas no such effect was observed when the participants' mental imagery was moderately or strongly suppressed. Collectively, these findings suggest that music may influence the food choices people make in virtual food choice tasks by inducing mental imagery, which provides insights into utilizing environmental cues to promote healthier food choices.

Combined Radiomics-Clinical Model to Predict Radiotherapy Response in Inoperable Stage III and IV Non-Small-Cell Lung Cancer.

Purpose: Radiotherapy is a promising treatment option for lung cancer, but patients' responses vary. The purpose of the study was to investigate the potential of radiomics and clinical signature for predicting the radiotherapy sensitivity and overall survival of inoperable stage III and IV non-small-cell lung cancer (NSCLC) patients. Materials: This retrospective study collected 104 inoperable stage III and IV NSCLC patients at the Yunnan Cancer Hospital from October 2016 to September 2020. They were divided into radiation-sensitive and non-sensitive groups. We used analysis of variance (ANOVA) to select features and support vector machine (SVM) to build the radiomic model. Furthermore, the logistic regression method was used to screen out clinically relevant predictive factors and construct the combined model of radiomics-clinical features. Finally, survival was estimated using the Kaplan-Meier method. Results: There were 40 patients in the radiation-sensitive group and 64 in the non-sensitive group. These patients were divided into training set (73 cases) and testing set (31 cases) according to the ratio of 7:3. Nine radiomics features and one clinical feature were significantly associated with radiotherapy sensitivity. Both the radiomics model and combined model have good predictive performance (the areas under the curve (AUC) values of the testing set were 0.864 (95% confidence interval [CI]: 0.683-0.996) and 0.868 (95% CI: 0.689-1.000), respectively). Only platelet level status was associated with overall survival. Conclusion: The combined model constructed based on radiomics and clinical features can effectively identify the radiation-sensitive population and provide valuable clinical information. Patients with higher platelet levels may have a poor prognosis.

A virtual reality-based study of color contrast to encourage more sustainable food choices.

In order to identify effective strategies to increase more environmentally friendly food choices, we conducted an experimental study to examine how the color contrast between the food and the background might influence people's choices between meat and vegetable dishes. Participants were instructed to choose three desirable dishes out of a choice set presented on a red- or green-colored table in a simulated restaurant environment. Each choice set consisted of two meat and two vegetable dishes, so the participants had to choose between the meat-heavy and vegetable-forward meals. The participants chose the meat-heavy meals more often than the chance level. However, the results revealed that using a red table to present the choice set could shift them toward choosing fewer meat-heavy meals and thus more vegetable-forward meals, and the visual attractiveness of the meat dishes was decreased when presented on the red tables. These findings provide empirical evidence regarding how the contrast between the color of food and the background color of the dining table can be used to modulate the sensory appeal of foods in order to promote sustainable food choices.

Cloud-Based Commensality: Enjoy the Company of Co-diners Without Social Facilitation of Eating.

Previous research has associated frequently enforced solo dining with negative consequences on psychological well-being, but the problem of having to eat alone may be solved by seeking mealtime companions in the digital space by watching an eating broadcast (i.e., Mukbang) or videoconferencing with others (i.e., cloud-based commensality). We conducted the present study to compare the consequences of Mukbang-based, cloud-based, and in-person commensality. Ninety-five healthy Chinese young adults were instructed to rate images of eating scenarios and foods. The results revealed that they expected loneliness to be reduced by Mukbang-based or in-person commensality, but they were also aware of the risks of enhancing food intake and/or being shifted toward less healthy food choices in these two scenarios. By contrast, the participants expected cloud-based commensality to provide the benefits of reducing loneliness without the health-compromising risks of increasing food intake or unhealthy eating. Collectively, these findings suggest the beliefs of the participants that cloud-based commensality can provide an "alone but together" context to balance the need for social interactions with the strategic avoidance of a social context facilitating unhealthy eating. The findings also provide some novel insights into how the application of technologies for eating behavior can be used to integrate social factors and food pleasure, and shed light on the promising future of cloud-based commensality as a combination of the strengths of solitary and commensal eating.